# This file is modified from https://github.com/haotian-liu/LLaVA/

"""Generate json file for webpage."""
import json
import os
import re

# models = ['llama', 'alpaca', 'gpt35', 'bard']
models = ["vicuna"]


def read_jsonl(path: str, key: str = None):
    data = []
    with open(os.path.expanduser(path)) as f:
        for line in f:
            if not line:
                continue
            data.append(json.loads(line))
    if key is not None:
        data.sort(key=lambda x: x[key])
        data = {item[key]: item for item in data}
    return data


def trim_hanging_lines(s: str, n: int) -> str:
    s = s.strip()
    for _ in range(n):
        s = s.split("\n", 1)[1].strip()
    return s


if __name__ == "__main__":
    questions = read_jsonl("table/question.jsonl", key="question_id")

    # alpaca_answers = read_jsonl('table/answer/answer_alpaca-13b.jsonl', key='question_id')
    # bard_answers = read_jsonl('table/answer/answer_bard.jsonl', key='question_id')
    # gpt35_answers = read_jsonl('table/answer/answer_gpt35.jsonl', key='question_id')
    # llama_answers = read_jsonl('table/answer/answer_llama-13b.jsonl', key='question_id')
    vicuna_answers = read_jsonl("table/answer/answer_vicuna-13b.jsonl", key="question_id")
    ours_answers = read_jsonl("table/results/llama-13b-hf-alpaca.jsonl", key="question_id")

    review_vicuna = read_jsonl("table/review/review_vicuna-13b_llama-13b-hf-alpaca.jsonl", key="question_id")
    # review_alpaca = read_jsonl('table/review/review_alpaca-13b_vicuna-13b.jsonl', key='question_id')
    # review_bard = read_jsonl('table/review/review_bard_vicuna-13b.jsonl', key='question_id')
    # review_gpt35 = read_jsonl('table/review/review_gpt35_vicuna-13b.jsonl', key='question_id')
    # review_llama = read_jsonl('table/review/review_llama-13b_vicuna-13b.jsonl', key='question_id')

    records = []
    for qid in questions.keys():
        r = {
            "id": qid,
            "category": questions[qid]["category"],
            "question": questions[qid]["text"],
            "answers": {
                # 'alpaca': alpaca_answers[qid]['text'],
                # 'llama': llama_answers[qid]['text'],
                # 'bard': bard_answers[qid]['text'],
                # 'gpt35': gpt35_answers[qid]['text'],
                "vicuna": vicuna_answers[qid]["text"],
                "ours": ours_answers[qid]["text"],
            },
            "evaluations": {
                # 'alpaca': review_alpaca[qid]['text'],
                # 'llama': review_llama[qid]['text'],
                # 'bard': review_bard[qid]['text'],
                "vicuna": review_vicuna[qid]["content"],
                # 'gpt35': review_gpt35[qid]['text'],
            },
            "scores": {
                "vicuna": review_vicuna[qid]["tuple"],
                # 'alpaca': review_alpaca[qid]['score'],
                # 'llama': review_llama[qid]['score'],
                # 'bard': review_bard[qid]['score'],
                # 'gpt35': review_gpt35[qid]['score'],
            },
        }

        # cleanup data
        cleaned_evals = {}
        for k, v in r["evaluations"].items():
            v = v.strip()
            lines = v.split("\n")
            # trim the first line if it's a pair of numbers
            if re.match(r"\d+[, ]+\d+", lines[0]):
                lines = lines[1:]
            v = "\n".join(lines)
            cleaned_evals[k] = v.replace("Assistant 1", "**Assistant 1**").replace("Assistant 2", "**Assistant 2**")

        r["evaluations"] = cleaned_evals
        records.append(r)

    # Reorder the records, this is optional
    for r in records:
        if r["id"] <= 20:
            r["id"] += 60
        else:
            r["id"] -= 20
    for r in records:
        if r["id"] <= 50:
            r["id"] += 10
        elif 50 < r["id"] <= 60:
            r["id"] -= 50
    for r in records:
        if r["id"] == 7:
            r["id"] = 1
        elif r["id"] < 7:
            r["id"] += 1

    records.sort(key=lambda x: x["id"])

    # Write to file
    with open("webpage/data.json", "w") as f:
        json.dump({"questions": records, "models": models}, f, indent=2)
